Questions
The La Puerta Bank of Stockholm City has one outside drive-up teller. It takes the teller...

The La Puerta Bank of Stockholm City has one outside drive-up teller. It takes the teller an average of 4 minutes to serve a bank customer. Customers arrive at the drive-up window at a rate of 12 per hour. The bank operations officer is currently analyzing the possibility of adding a second drive-up window, at an annual cost of Php 1,000,000. It is assumed that arriving cars would be equally divided between both windows. The operations officer estimates that each minute's reduction in customer waiting time would increase the bank's revenue by Php 100,000 annually. Should the second drive-up window be installed? Show computations that will prove your claim.

In: Operations Management

1. Individual Problems 14-1 Suppose Mattel, the producer of Barbie dolls and accessories (sold separately), has...

1. Individual Problems 14-1

Suppose Mattel, the producer of Barbie dolls and accessories (sold separately), has two types of consumers who purchase its dolls: low-value consumers and high-value consumers. Each of the low-value consumers tends to purchase one doll and one accessory, with a total willingness to pay of $56. Each of the high-value consumers buys one doll and two accessories and is willing to pay $109 in total.

Mattel is currently considering two pricing strategies:

Strategy 1: Sell each doll for $28 and each accessory for $28
Strategy 2: Sell each doll for $3 and each accessory for $53

In the following table, indicate the revenue for a low-value and a high-value customer under strategy 1 and strategy 2. Then, assuming each strategy is applied to one low-value and one high-value customer, indicate the total revenue for each strategy.

Revenue from Low-Value Customers

Revenue from High-Value Customers

Total Revenue from Strategy

$56 Value, 1 Accessory

$109 Value, 2 Accessories

($)

($)

($)

Strategy 1
$28 doll + $28 accessory

?

?

?

Strategy 2
$3 doll + $53 accessory

?

?

?

The strategy that generates the most revenue is strategy is (?)

In: Economics

In the differences between the male versus female urinary tract. EXPLAIN anatomically why one sex has...

In the differences between the male versus female urinary tract. EXPLAIN anatomically why one sex has a higher risk of lower urinary tract inflammation or infections. In your explanation, compare the male versus female lower urinary tract including length, locations & nearby organs that might contribute to inflammation or infection?

In: Anatomy and Physiology

?       How does chronic hyperglycemia effect ?       high-density lipoproteins (HDLs) ?       low-density lipoproteins (LDLs) ?      

?       How does chronic hyperglycemia effect

?       high-density lipoproteins (HDLs)

?       low-density lipoproteins (LDLs)

?       triglycerides

?       How do these changes contribute to coronary artery disease?

?       How does increased platelet aggregation among those with diabetes affect vascular health?

?       What is the correlation between hypertension and diabetic complications?

In: Nursing

Explain how the balance of payments situation and the non-convertible nature of the Chinese Yuan (Renminbi)...

Explain how the balance of payments situation and the non-convertible nature of the Chinese Yuan (Renminbi) has influenced the current trade dispute between China and the U.S.A.

How might differences in a countries political ideology influence its policy with respect to protection of intellectual property rights? Why might this contribute to trade disputes?

In: Economics

The physical plant at the main campus of a large state university recieves daily requests to...

The physical plant at the main campus of a large state university recieves daily requests to replace florecent lightbulbs. The distribution of the number of daily requests is bell-shaped and has a mean of 53 and a standard deviation of 7. Using the 68-95-99.7 rule, what is the approximate percentage of lightbulb replacement requests numbering between 53 and 74?

In: Statistics and Probability

Your driving time to work  (continuous random variable) is between 27 and 69 minutes if the day...

Your driving time to work  (continuous random variable) is between 27 and 69 minutes if the day is sunny, and between 47 and 87 minutes if the day is rainy, with a uniform probability density function in the given range in each case.

Assume that a day is sunny with probability  = 0.83 and rainy with probability .

Your distance to work is  = 50 kilometers. Let  be your average speed for the drive to work, measured in kilometers per minute:

Compute the value of the probability density function (PDF) of the average speed  at  = 0.69

Round your answer to five decimal digits after the decimal point.

In: Statistics and Probability

The temperature in degrees Fahrenheit and the number of emergency calls are shown below. Determine if...

The temperature in degrees Fahrenheit and the number of emergency calls are shown below. Determine if there is a relationship between the temperature and the number of emergency calls received. Use .05 significance.

Number of Calls (Y)

Temperature (X)

7

68

4

74

8

82

10

88

11

93

9

99

13

101


What is the p value and is it significant?

Select one:

a. .1898, no it is not significant.

b. .0267, yes it is significant.

c. .2162, yes it is significant.

d. 9.6335, yes it is significant.

The temperature in degrees Fahrenheit and the number of emergency calls are shown below. Determine if there is a relationship between the temperature and the number of emergency calls received. Use .05 significance.

Number of Calls (Y)

Temperature (X)

7

68

4

74

8

82

10

88

11

93

9

99

13

101

If x is equal to 80, what is the value of y?

Select one:

a. Unable to determine because the relationship is not significant.

b. 7.0.

c. 7.6399.

d. 8.1088.

In: Statistics and Probability

According to a study done by De Anza students, the height for Asian adult males is...

According to a study done by De Anza students, the height for Asian adult males is normally distributed with an average of 66 inches and a standard deviation of 2.5 inches. Suppose one Asian adult male is randomly chosen. Let X = height of the individual.

Part B.

Find the probability that the person is between 64 and 69 inches.

Write the probability statement.

What is the probability? (Round your answer to four decimal places.)

Sketch the graph.

Part C.

Would you expect to meet many Asian adult males over 74 inches? Explain why or why not, and justify your answer numerically.

---Select--- Yes No , because the probability that an Asian male is over 74 inches tall is.

Part D.

The middle 40% of heights fall between what two values?

Write the probability statement.

P(x1 < X < x2) =

State the two values. (Round your answers to one decimal place.)

x1 =
x2 =


Sketch the graph.

In: Statistics and Probability

Assume you are a Data Analyst in an international economic consultancy firm. Your team leader has...

Assume you are a Data Analyst in an international economic consultancy firm. Your team leader has given you a research task to investigate the empirical relationship between China’s export volumes and per capita GDP (Gross Domestic Product).
Relevant Variables: China’s Export volume index and China’s GDP per capita (constant 2010 US$).
(Annual time series data (for the period 1980 – 2018) from the World Bank - World development indicators database)
The data are stored in the file named “ASSIGNMENTDATA.XLSX” in the course website. Using EXCEL, answer below questions:
1. Using an appropriate graphical descriptive measure (relevant for time series data) describe the two variables (1 mark)
2. Use an appropriate plot to investigate the relationship between Export volume index and GDP per capita. Assume Export volume index as an independent variable. Interpret the plot.
3. Prepare a numerical summary report about the data on the two variables by including the summary measures, mean, median, range, variance, standard deviation, coefficient of variation, smallest and largest values, and the three quartiles, for each variable.
4. Calculate the coefficient of correlation (r) between Export volume index and GDP per capita. Then, interpret it.
Page 3 of 4

5. Estimate a simple linear regression model and present the estimated linear equation. Then, interpret the coefficient estimates of the linear model.
6. Determine the coefficient of determination R2 and interpret it.
7. Test whether GDP per capita positively and significantly increases with
export volume index at the 5% significance level.
8. What is the value of the standard error of the estimate (se). Then,
comment on the fitness of the linear regression model? (1 mark)

Country Name China
Year
Export volume index
GDP per capita (constant 2010 US$)
1980 7.190964398 347.1200879
1981 8.743517899 360.4279678
1982 9.428373444 386.8903417
1983 10.25153246 422.6591909
1984 12.34004595 480.3028638
1985 12.61492904 537.5026526
1986 15.52047929 576.9087566
1987 18.40145453 634.092911
1988 21.66725703 694.0647918
1989 22.42809652 712.1153633
1990 25.6864244 729.1606454
1991 29.44489072 786.1296588
1992 34.0846619 886.9503589
1993 37.95357331 998.4047893
1994 48.55720035 1116.032535
1995 56.85936289 1224.848821
1996 56.64713312 1332.417309
1997 67.91726097 1440.59025
1998 70.88444114 1538.662844
1999 77.44729803 1642.357488
2000 100 1767.833627
2001 109.694188 1901.40763
2002 138.6582488 2061.162284
2003 182.785201 2253.929689
2004 226.8347239 2467.132843
2005 283.6441931 2732.16588
2006 346.1719795 3062.534905
2007 414.8560285 3480.152725
2008 450.2958821 3796.633363
2009 403.192961 4132.902312
2010 516.4926068 4550.453596
2011 561.8922874 4961.234689
2012 596.8391727 5325.160106
2013 647.4202795 5710.587873
2014 684.4722854 6096.487817
2015 680.5921485 6484.435948
2016 690.2482661 6883.895425
2017 738.9259384 7308.065366
2018 769.5482696 7754.962119

In: Statistics and Probability